ShelfAudit

ShelfAudit is a mobile + web AI computer-vision app for retail teams to audit shelves using quick aisle photos. Store associates snap a few images per bay; the system detects out-of-stocks, misplaced items, missing facings, and price-tag mismatches by comparing what it sees to the planogram and expected SKU list. It generates a prioritized task list (restock, reface, correct label) with annotated images as proof, and exports issues to existing ticketing/work-order tools. This is realistic because it focuses on a narrow, high-value workflow (shelf compliance) rather than trying to “understand the whole store.” The MVP can start with a limited SKU set and a single category (e.g., beverages) and improve over time with active learning from user confirmations. It’s an AI app plus traditional workflow software (tasks, roles, reporting).